Influence of the C161T but not Pro12Ala polymorphism in the peroxisome proliferator‐activated receptor‐gamma on colorectal cancer in an Indian population
Bibliographic record
Abstract
The aim of the present study was to investigate associations between Pro12Ala and C161T polymorphisms in the peroxisome proliferator-activated receptor-gamma (PPAR-gamma) gene and colorectal cancer (CRC) risk. We recruited 301 newly diagnosed CRC patients and 291 healthy control subjects at the Madras Cancer Institute in Chennai, India, from 1999 to 2001. Genotypes of the Pro12Ala and C161T polymorphisms were determined using the PCR-RFLP method. After adjustment for age, sex, smoking habit, family history and family income, an increased risk of CRC was observed for the C/T + T/T genotype compared to the C/C genotype of the C161T polymorphism (odds ratio = 1.61, 95% confidence interval: 1.10-2.36), whereas no significant association was found for Pro12Ala (odds ratio = 1.06, 95% confidence interval: 0.70-1.61). Analysis with estimated haplotypes showed a significant difference in haplotype frequencies between cases and controls (chi(2) = 11.62, P = 0.009, d.f. = 3). The relationship between the two polymorphisms and CRC risk was not significantly modified by dietary intake of fish. Although the biological mechanisms of the observed association remain to be elucidated, our findings suggest that the C161T polymorphism of the PPAR-gamma gene is related to risk of CRC. Further research is needed to investigate functional implications of polymorphisms of the PPAR-gamma gene in CRC development.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".